The actual utilization of network resources in a network (e.g., wide area network (WAN) such as a backbone network) is not easy to measure, let alone predict or control. The actual utilization may change quickly in time and in space, and it is hard to draw decisive conclusions by looking on summary statistics. However, hard as it may be, understanding the utilization pattern is a crucial first step when considering ways to optimize a network and is therefore important both from the operations point of view as well as for cost saving.
Traditionally, a main parameter used to describe network utilization is link utilization. For each link, utilization is defined as the amount of traffic traversing the link divided by the link capacity. Since modern networks consist of many links, the (weighted) average of the link utilization is used as a single number representing network utilization. Note that the time frame here may be important since the average utilization of a link over short time periods may be very noisy. For performance management usage, for example, it is common to average link utilization over five minute periods.
While link utilization is one metric and indeed provides meaningful information, link utilization may not always be sufficient. First, examining some percentiles or max link utilization does not provide enough information. It is not clear how to evaluate a given maximal link utilization. What really matters is the link utilization distribution over all the network links and over time.
Second, link utilization does not necessarily reflect network performance, as it is possible and even common for the link utilization to be much lower than the actual traffic, due to built in redundancy (addressing possible failures) and in order to allow flows (demands) to grow. The additional traffic that the network can really accommodate depends on the specific traffic engineering (TE) used as well as on the utilization of links and on the demand pattern. Finally, the link utilization does not tell the story from the client side, and does not describe how any specific user is experiencing the network. Therefore, it is desirable to devise other techniques to measure network utilization.